How Spatial Patterns of Soil Moisture Dynamics Can Explain Field‐Scale Soil Moisture Variability: Observations From a Sodic Landscape

Abstract

Root‐zone soil moisture (0–110 cm) was monitored at 21 sites within a cold‐region semiarid prairie grazing pasture over multiple growing seasons. There were large differences in the moisture dynamics for different sites, which was related to local‐scale impacts of sodium‐induced clay dispersion. Sites with high exchangeable sodium percentages, indicative of sodic soils, were characterized by small changes in soil moisture storage. The sites with the largest soil moisture changes had negligible exchangeable sodium percentage. We used this difference to divide the area into sites that participate in the field‐scale water balance and those that do not. As a result of this heterogeneity, a unique soil moisture variability‐mean relationship was observed; the spatial variability of root‐zone soil moisture was lowest during intermediate wetness conditions and highest for wet and dry conditions. Furthermore, the shape of the variability‐mean relationship depended on the depth over which soil moisture was integrated. The persistent differences in soil moisture dynamics were also responsible for the presence of two distinct spatial patterns of root‐zone soil moisture, representing early and late growing season (i.e., wet and dry conditions). The participating versus nonparticipating framework may be applicable broadly to sodic soils and to other soil types and has practical implications for parameterizing the water balance in hydrological models and for designing representative soil moisture monitoring networks in such environments.

The role of landscape morphology on soil moisture variability in semi‐arid ecosystems

“…For ease of visualization, results for each time step (a year) are binned in 〈 θ 〉 intervals of 0.02. The binned results from all the soil moisture controlling factors show a same convex parabolic CV 〈 θ 〉 − 〈 θ 〉 relationship than observed in Figure 4, which is consistent with previous studies in semi‐arid regions (Fatichi et al, 2015; Ivanov et al, 2010; Mascaro & Vivoni, 2016; Peterson et al, 2019; Western et al, 2003). The higher values of 〈 θ 〉 reflect near saturation conditions in the domain, whilst intermediate values of 〈 θ 〉 indicate both wetting and drying periods, and low values indicates the inter‐storm period.…”

“…The convex shape for the CV 〈 θ 〉 − 〈 θ 〉 relation obtained from our simulations ( Figures 4 and 5, S1 and S2), is consistent with previous studies in semi‐arid regions (Fatichi et al, 2015; Ivanov et al, 2010; Mascaro & Vivoni, 2016; Peterson et al, 2019; Western et al, 2003). The variability of soil moisture is higher in periods with relatively dry conditions but not completely dry.…”

Near-surface soil moisture dynamics in a prairie hillslope seep/headwater stream system in Texas, USA

“…Additionally, our results verified that the footslope remained relatively wetter than the rest of the hillslope after a precipitation event, indicating a concentration of water draining downslope of the barrens (Llado & Slattery, 2015;Tromp-van Meerveld & McDonnell, 2006a;Western et al, 2004). This is consistent with other studies that correlate topography with saturation and downslope migration of water into deeper, clay-rich soils at the footslope, but that other factors may better explain the spatial variability of soil moisture across the hillslope (Peterson et al, 2019;Wilson et al, 2004). When compared to data from Llado and Slattery (2015), our results show a similar θ v drying curve along the transect; however, our results show more variability and skewness toward low θ v in the interquartile range, but consistently higher means for all probes.…”

Spatiotemporal dynamics and interrelationship between soil moisture and groundwater over the Critical Zone Observatory in the Central Ganga plain, North India

“…The concave upward relation between ̅ and and convex upward relationship between ̅ and in the SM dynamics in Fig. 5a have been observed from numerical studies across various climatic domains (Brocca et al, 2010(Brocca et al, , 2012Peterson et al, 2019). Further, the obtained relationship is also convincing for the DTGT observations (Fig.…”